Data Security

3:00 PM – Cybersecurity Architecture for Telemetry Networks: Development of a Comprehensive Cybersecurity Framework for Industrial Control Systems (ICS) and SCADA Networks
Moses Odejobi, Morgan State University; Advisors: Dr. Arlene Cole-Rhodes, Dr. Richard Dean, Dr. Farzad Moazzami, and Dr. Craig Scott, Morgan State University

Telemetry systems in critical infrastructure face unprecedented cybersecurity challenges as industrial networks become increasingly interconnected. This paper presents an advanced telemetry security assessment framework implementing a comprehensive Industrial Control System (ICS) cybersecurity simulation platform based on the Purdue Model architecture. The platform provides realistic threat analysis capabilities and defense strategy validation for telemetry-enabled industrial environments. Our implementation features real-time network communication across six Purdue levels, cross-level attack propagation simulation, and interactive threat storytelling capabilities. A unique feature of the system is its ability to detect attacks that originate as internal lateral movements as well as those that are from internetfacing services, thereby demonstrating real-time attack scenarios. Validation of the experiment in this work is executed using two-dozens of simulated devices across all Purdue levels, with the results revealing 94% efficiency for security controls. Web platforms adopted include PostgreSQL database integration, OpenPLC runtime integration among others. Study results indicate the usefulness of cybersecurity training and implementation.

3:20 PM – Mitigating Generative Artificial Intelligence (AI) Cybersecurity Risks Leveraging Retrieval Augmented Generation (RAG) in Telemetry Post Processing Analysis
Jeff Kalibjian, Peraton

Using AI tools to assist in telemetry post processing analysis can offload tedious analysis tasks as well as provide opportunities for gaining better and new insights into interpreting data. However, deploying generative AI applications into sensitive telemetry post processing environments can introduce significant cybersecurity risks; specifically, with respect to generative AI models potentially integrating sensitive program data into the underlying model being used. If configured properly, Retrieval Augmented Generation (RAG) provides a capability for generative AI solutions to leverage important information that will not be integrated into the fundamental AI model being utilized. After reviewing the current generative AI threat landscape, examples will be given regarding how RAG may be employed to better mitigate generative AI cybersecurity risks in telemetry post processing environments.

3:40 PM- Applying Post-Quantum Cryptography Based on Quasi-Cyclic Codes to Aeronautical Mobile Telemetry
Benjamin Arnesen, Trevor Wai, Tyler Randall, and Willie Harrison, Brigham Young University;Yuxing Yang, University of Illinois; David Mitchell, New Mexico State University

The vulnerability of asymmetric cryptosystems to sufficiently-powerful quantum computers has propelled the rise of post-quantum cryptography (PQC). Several cryptographic algorithms have proven promising candidates for replacing the current algorithms that are susceptible to quantum attacks. Among these candidates are public-key cryptosystems (PKCs) that are based on error-correcting codes. PKCs can be wrapped in key encapsulation mechanisms (KEMs), which are recommended for post-quantum applications. We provide necessary background and explore two code-based KEMs based on quasi-cyclic codes: Bit Flipping Key Encapsulation and Hamming Quasi-Cyclic. Both KEMs were submitted to the fourth round of the National Institute of Standards and Technology’s PQC standardization process. For each KEM, we discuss the included algorithms, key sizes, and known attacks. We also show how these KEMs can be used in aeronautical mobile telemetry to distribute symmetric Advanced Encryption Standard keys.

4:00 PM – Automating Cloud Security with Policy as Code: A Case Study on AWS S3 Buckets
Katlyn Cox and Dr. Farzad Moazzami, Morgan State University

As cloud adoption grows and threats evolve, enforcing consistent and scalable security policies is increasingly challenging. Policy as Code (PaC) addresses this by enabling the definition, management, and automation of security policies through code. This paper explores PaC’s role in automating cloud security, with a focus on AWS environments. It highlights how integrating PaC into DevSecOps pipelines reduces misconfigurations, enhances transparency, and supports real-time compliance. Using a case study of AWS S3 buckets—often misconfigured in public and government sectors—this research demonstrates how tools like AWS CloudFormation Guard, Open Policy Agent (OPA), and CI/CD pipelines can enforce policies for secure and compliant configurations. These include checks for public access, encryption, and role-based access. The paper proposes a practical framework for scalable, testable, and auditable cloud governance using Policy as Code.

4:20 PM-  Enhancing Cybersecurity with Removable Non-Volatile Memory in  FTI  Systems    
Markus Mazur and Stefan Grüter, Safran Data Systems GmbH

This approach introduces a security concept for FTI devices based on a Removable Secure Operational Disk (RSOD) containing all non-volatile memory of the FTI system, excluding storage devices. The RSOD functions as the device’s only persistent memory, containing all security-critical information, including the operating system, firmware, environmental data, MAC addresses and user configuration. The option of using data encryption and secure boot mechanisms ensures a high level of protection against tampering. Removing the RSOD leads to a declassification of the device (e.g. for maintenance work), as all sensitive data is stored exclusively on the RSOD. The architecture opens up additional security, operational advantages and simplified export regulations. For instance, firmware and system updates can be carried out by removing the RSOD and updating it externally under controlled conditions. In addition, the duplication of existing RSODs enables the efficient distribution of configurations across multiple devices. This allows for consistent system deployment as well as time-optimized use in multiple devices. Finally, because of the modular and interchangeable design, system capacity can be flexibly scaled by only upgrading the RSOD, providing an adaptable and future-proof system architecture.